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Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players

Injuries are one of the most significant issues for elite football players. Consequently, elite football clubs have been consistently interested in having practical, interpretable, and usable models as decision-making support for technical staff. This study aimed to analyze predictive modeling of in...

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Autores principales: Martins, Francisco, Przednowek, Krzysztof, França, Cíntia, Lopes, Helder, de Maio Nascimento, Marcelo, Sarmento, Hugo, Marques, Adilson, Ihle, Andreas, Henriques, Ricardo, Gouveia, Élvio Rúbio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9409763/
https://www.ncbi.nlm.nih.gov/pubmed/36013162
http://dx.doi.org/10.3390/jcm11164923
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author Martins, Francisco
Przednowek, Krzysztof
França, Cíntia
Lopes, Helder
de Maio Nascimento, Marcelo
Sarmento, Hugo
Marques, Adilson
Ihle, Andreas
Henriques, Ricardo
Gouveia, Élvio Rúbio
author_facet Martins, Francisco
Przednowek, Krzysztof
França, Cíntia
Lopes, Helder
de Maio Nascimento, Marcelo
Sarmento, Hugo
Marques, Adilson
Ihle, Andreas
Henriques, Ricardo
Gouveia, Élvio Rúbio
author_sort Martins, Francisco
collection PubMed
description Injuries are one of the most significant issues for elite football players. Consequently, elite football clubs have been consistently interested in having practical, interpretable, and usable models as decision-making support for technical staff. This study aimed to analyze predictive modeling of injury risk based on body composition variables and selected physical fitness tests for elite football players through a sports season. The sample comprised 36 male elite football players who competed in the First Portuguese Soccer League in the 2020/2021 season. The models were calculated based on 22 independent variables that included players’ information, body composition, physical fitness, and one dependent variable, the number of injuries per season. In the net elastic analysis, the variables that best predicted injury risk were sectorial positions (defensive and forward), body height, sit-and-reach performance, 1 min number of push-ups, handgrip strength, and 35 m linear speed. This study considered multiple-input single-output regression-type models. The analysis showed that the most accurate model presented in this work generates an error of RMSE = 0.591. Our approach opens a novel perspective for injury prevention and training monitorization. Nevertheless, more studies are needed to identify risk factors associated with injury prediction in elite soccer players, as this is a rising topic that requires several analyses performed in different contexts.
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spelling pubmed-94097632022-08-26 Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players Martins, Francisco Przednowek, Krzysztof França, Cíntia Lopes, Helder de Maio Nascimento, Marcelo Sarmento, Hugo Marques, Adilson Ihle, Andreas Henriques, Ricardo Gouveia, Élvio Rúbio J Clin Med Article Injuries are one of the most significant issues for elite football players. Consequently, elite football clubs have been consistently interested in having practical, interpretable, and usable models as decision-making support for technical staff. This study aimed to analyze predictive modeling of injury risk based on body composition variables and selected physical fitness tests for elite football players through a sports season. The sample comprised 36 male elite football players who competed in the First Portuguese Soccer League in the 2020/2021 season. The models were calculated based on 22 independent variables that included players’ information, body composition, physical fitness, and one dependent variable, the number of injuries per season. In the net elastic analysis, the variables that best predicted injury risk were sectorial positions (defensive and forward), body height, sit-and-reach performance, 1 min number of push-ups, handgrip strength, and 35 m linear speed. This study considered multiple-input single-output regression-type models. The analysis showed that the most accurate model presented in this work generates an error of RMSE = 0.591. Our approach opens a novel perspective for injury prevention and training monitorization. Nevertheless, more studies are needed to identify risk factors associated with injury prediction in elite soccer players, as this is a rising topic that requires several analyses performed in different contexts. MDPI 2022-08-22 /pmc/articles/PMC9409763/ /pubmed/36013162 http://dx.doi.org/10.3390/jcm11164923 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Martins, Francisco
Przednowek, Krzysztof
França, Cíntia
Lopes, Helder
de Maio Nascimento, Marcelo
Sarmento, Hugo
Marques, Adilson
Ihle, Andreas
Henriques, Ricardo
Gouveia, Élvio Rúbio
Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players
title Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players
title_full Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players
title_fullStr Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players
title_full_unstemmed Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players
title_short Predictive Modeling of Injury Risk Based on Body Composition and Selected Physical Fitness Tests for Elite Football Players
title_sort predictive modeling of injury risk based on body composition and selected physical fitness tests for elite football players
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9409763/
https://www.ncbi.nlm.nih.gov/pubmed/36013162
http://dx.doi.org/10.3390/jcm11164923
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